| 2024 | Second Order Methods for Bandit Optimization and Control. | Arun Suggala, Y. Jennifer Sun, Praneeth Netrapalli, Elad Hazan |
| 2024 | A non-backtracking method for long matrix and tensor completion. | Ludovic Stephan, Yizhe Zhu |
| 2024 | Fast sampling from constrained spaces using the Metropolis-adjusted Mirror Langevin algorithm. | Vishwak Srinivasan, Andre Wibisono, Ashia C. Wilson |
| 2024 | A Non-Adaptive Algorithm for the Quantitative Group Testing Problem. | Mahdi Soleymani, Tara Javidi |
| 2024 | Improved High-Probability Bounds for the Temporal Difference Learning Algorithm via Exponential Stability. | Sergey Samsonov, Daniil Tiapkin, Alexey Naumov, Eric Moulines |
| 2024 | Provable Advantage in Quantum PAC Learning. | Wilfred Salmon, Sergii Strelchuk, Tom Gur |
| 2024 | Online Structured Prediction with Fenchel-Young Losses and Improved Surrogate Regret for Online Multiclass Classification with Logistic Loss. | Shinsaku Sakaue, Han Bao, Taira Tsuchiya, Taihei Oki |
| 2024 | Online Learning with Set-valued Feedback. | Vinod Raman, Unique Subedi, Ambuj Tewari |
| 2024 | Apple Tasting: Combinatorial Dimensions and Minimax Rates. | Vinod Raman, Unique Subedi, Ananth Raman, Ambuj Tewari |
| 2024 | Fit Like You Sample: Sample-Efficient Generalized Score Matching from Fast Mixing Diffusions. | Yilong Qin, Andrej Risteski |
| 2024 | On the Distance from Calibration in Sequential Prediction. | Mingda Qiao, Letian Zheng |
| 2024 | Dimension-free Structured Covariance Estimation. | Nikita Puchkin, Maxim V. Rakhuba |
| 2024 | Sample-Optimal Locally Private Hypothesis Selection and the Provable Benefits of Interactivity. | Alireza Fathollah Pour, Hassan Ashtiani, Shahab Asoodeh |
| 2024 | Smooth Lower Bounds for Differentially Private Algorithms via Padding-and-Permuting Fingerprinting Codes. | Naty Peter, Eliad Tsfadia, Jonathan R. Ullman |
| 2024 | The Sample Complexity of Simple Binary Hypothesis Testing. | Ankit Pensia, Varun S. Jog, Po-Ling Loh |
| 2024 | The complexity of approximate (coarse) correlated equilibrium for incomplete information games. | Binghui Peng, Aviad Rubinstein |
| 2024 | The sample complexity of multi-distribution learning. | Binghui Peng |
| 2024 | The Limits and Potentials of Local SGD for Distributed Heterogeneous Learning with Intermittent Communication. | Kumar Kshitij Patel, Margalit Glasgow, Ali Zindari, Lingxiao Wang, Sebastian U. Stich, Ziheng Cheng, Nirmit Joshi, Nathan Srebro |
| 2024 | Depth Separation in Norm-Bounded Infinite-Width Neural Networks. | Suzanna Parkinson, Greg Ongie, Rebecca Willett, Ohad Shamir, Nathan Srebro |
| 2024 | Learning sum of diverse features: computational hardness and efficient gradient-based training for ridge combinations. | Kazusato Oko, Yujin Song, Taiji Suzuki, Denny Wu |
| 2024 | Robust Distribution Learning with Local and Global Adversarial Corruptions (extended abstract). | Sloan Nietert, Ziv Goldfeld, Soroosh Shafiee |
| 2024 | Optimistic Information Directed Sampling. | Gergely Neu, Matteo Papini, Ludovic Schwartz |
| 2024 | Exact Mean Square Linear Stability Analysis for SGD. | Rotem Mulayoff, Tomer Michaeli |
| 2024 | Finding Super-spreaders in Network Cascades. | Elchanan Mossel, Anirudh Sridhar |
| 2024 | Fundamental Limits of Non-Linear Low-Rank Matrix Estimation. | Pierre Mergny, Justin Ko, Florent Krzakala, Lenka Zdeborov |